Text-to-Image
Diffusers
Safetensors
LensPipeline
lens
sdnq
uint4
static-quantization
ablation
model-cpu-offload
Instructions to use WaveCut/Lens-SDNQ-uint4-static with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use WaveCut/Lens-SDNQ-uint4-static with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("WaveCut/Lens-SDNQ-uint4-static", dtype=torch.bfloat16, device_map="cuda") prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps
- Draw Things
- DiffusionBee
- Xet hash:
- 72848b90c614d46385412e759b550cfe630bd439fe7f66097e4341749cf71c5d
- Size of remote file:
- 16.1 MB
- SHA256:
- 16ff57dc58c48f438e786bd41502a2f5aa36646f55763cdc3b3e6d957cf46dc5
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